Cargando…
Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals
The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded duri...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9000342/ https://www.ncbi.nlm.nih.gov/pubmed/35407991 http://dx.doi.org/10.3390/ma15072659 |
_version_ | 1784685410798010368 |
---|---|
author | Świt, Grzegorz Dzioba, Ihor Adamczak-Bugno, Anna Krampikowska, Aleksandra |
author_facet | Świt, Grzegorz Dzioba, Ihor Adamczak-Bugno, Anna Krampikowska, Aleksandra |
author_sort | Świt, Grzegorz |
collection | PubMed |
description | The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage. |
format | Online Article Text |
id | pubmed-9000342 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90003422022-04-12 Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals Świt, Grzegorz Dzioba, Ihor Adamczak-Bugno, Anna Krampikowska, Aleksandra Materials (Basel) Article The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage. MDPI 2022-04-04 /pmc/articles/PMC9000342/ /pubmed/35407991 http://dx.doi.org/10.3390/ma15072659 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Świt, Grzegorz Dzioba, Ihor Adamczak-Bugno, Anna Krampikowska, Aleksandra Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals |
title | Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals |
title_full | Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals |
title_fullStr | Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals |
title_full_unstemmed | Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals |
title_short | Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals |
title_sort | identification of the fracture process in gas pipeline steel based on the analysis of ae signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9000342/ https://www.ncbi.nlm.nih.gov/pubmed/35407991 http://dx.doi.org/10.3390/ma15072659 |
work_keys_str_mv | AT switgrzegorz identificationofthefractureprocessingaspipelinesteelbasedontheanalysisofaesignals AT dziobaihor identificationofthefractureprocessingaspipelinesteelbasedontheanalysisofaesignals AT adamczakbugnoanna identificationofthefractureprocessingaspipelinesteelbasedontheanalysisofaesignals AT krampikowskaaleksandra identificationofthefractureprocessingaspipelinesteelbasedontheanalysisofaesignals |